We’re have five big publications to share, spanning #GenerativeAI to protein folding. You can see more here https://
bit.ly/3VwZyt7 2/4
AI
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Five Major Publications on Generative AI and Protein Folding
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Upcoming Presentations and Booth Events This Week
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Throughout the week we’ll be sharing more on our latest work, a few upcoming presentations at our booth that you won't want to miss. Tue, 9am: Casual Conversations Tue, 1:30pm: CICERO Wed, 9am: @PyTorch TorchMultimodal Wed, 1:30pm: ESM Metagenomic Atlas 3/4
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Meta AI Team at NeurIPS 2022 Conference Booth 208
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👋Hey #NeurIPS2022! We’re here and excited to connect and share with the community over the course of the conference.
— AI at Meta (@AIatMeta) 28 novembre 2022
📍 Booth #208
A 🧵of things to look out for from the Meta AI team ⬇️
1/4 pic.twitter.com/E4pyf3YTMTHey #NeurIPS2022! We’re here and excited to connect and share with the community over the course of the conference. Booth #208 A of things to look out for from the Meta AI team 1/4
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Create Custom Memory Modules for LangChain Chains
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And here's how you can create your own custom memory module! https://
langchain.readthedocs.io/en/latest/exam
ples/memory/custom_memory.html
… This can be used to implement your own ideal memory structure and then easily plug it into any chain. -
Expanding Memory Types in LangChain With Community Contributions
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There are many more types of memory we hope to add! @sjwhitmore has been pioneering this effort so far, and we hope a lot of these come from the community. Check out this idea from @BrennanErbz for inspiration
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Contribute Memory Implementations to LangChain Core Library
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If you do have a memory implementation you think is generally useful, we'd LOVE to have it contributed back into the core library! We are super excited to see what people build with this https://
github.com/hwchase17/lang
chain
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Getting Started with Memory in Conversation Chains
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Here is a notebook for getting started with memory. It walks through maybe the most clear application of memory: a conversation chain. It showcases short term memory – remembering the conversation to date https://
langchain.readthedocs.io/en/latest/gett
ing_started/memory.html
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Add Memory to Any LLM Chain and Agent
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But you don't just have to use the predefined conversation chain! Here's how you can add memory to any LLM chain: https://
langchain.readthedocs.io/en/latest/exam
ples/memory/adding_memory.html
… And here's how you can add memory to an agent: https://
langchain.readthedocs.io/en/latest/exam
ples/memory/agent_with_memory.html
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LangChain Chains Now Support Stateful Conversations and Memory
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So far all the chains/agents in LangChain have been stateless, meaning each interaction is independent This is far from ideal for some real world settings (eg chatbots) where you want the chain/agent to remember previous conversations
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Memory Module: Loading and Saving Data in Chains
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To achieve this, we added the the concept of a memory module This module: Loads things from memory before passing user input to the chain Saves things to memory after the chain is finished